[1] Lan Zhuorui, Xia Weiwei, Wu Siyun, Yan Feng, et al. Joint wireless and cloud resource allocationbased on parallel auction for mobile edge computing [J]. Journal of Southeast University (English Edition), 2019, 35 (2): 153-159. [doi:10.3969/j.issn.1003-7985.2019.02.002]

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Joint wireless and cloud resource allocationbased on parallel auction for mobile edge computing()

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

35

Issue:

2019 2

Page:

153-159

Research Field:

Information and Communication Engineering

Publishing date:

2019-06-30

Info

Title:

Joint wireless and cloud resource allocationbased on parallel auction for mobile edge computing

Author(s):

Lan Zhuorui;  Xia Weiwei;  Wu Siyun;  Yan Feng;  Shen Lianfeng

National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China

Keywords:

parallel auction;  mobile edge computing;  joint resource allocation;  fast matching

PACS:

TN929.5

DOI:

10.3969/j.issn.1003-7985.2019.02.002

Abstract:

A joint resource allocation algorithm based on parallel auction(JRAPA)is proposed for mobile edge computing(MEC). In JRAPA, the joint allocation of wireless and cloud resources is modeled as an auction process, aiming at maximizing the utilities of service providers(SPs)and satisfying the delay requirements of mobile terminals(MTs). The auction process consists of the bidding submission, winner determination and pricing stages. At the bidding submission stage, the MTs take available resources from SPs and distance factors into account to decide the bidding priority, thereby reducing the processing delay and improving the successful trades rate. A resource constrained utility ranking(RCUR)algorithm is put forward at the winner determination stage to determine the winners and losers so as to maximize the utilities of SPs. At the pricing stage, the sealed second-price rule is adopted to ensure the independence between the price paid by the buyer and its own bid. The simulation results show that the proposed JRAPA algorithm outperforms other existing algorithms in terms of the convergence rate and the number of successful trades rate. Moreover, it can not only achieve a larger average utility of SPs but also significantly reduce the average delay of MTs.

References:

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Memo

Memo:

Biographies: Lan Zhuorui(1994—), female, graduate; Xia Weiwei(corresponding author), female, doctor, associate professor, wwxia@seu.edu.cn.
Foundation item: The National Natural Science Foundation of China(No.61741102, 61471164, 61601122).
Citation: Lan Zhuorui, Xia Weiwei, Wu Siyun, et al.Joint wireless and cloud resource allocation based on parallel auction for mobile edge computing[J].Journal of Southeast University(English Edition), 2019, 35(2):153-159.DOI:10.3969/j.issn.1003-7985.2019.02.002.

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